Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.3%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: NicholasSynovic
- License: agpl-3.0
- Language: Python
- Default Branch: main
- Size: 776 KB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
ScODA: Supercomputing Operational Data Analytics Database Benchmarking
An emerging pipeline for evaluating distributed database performance
Table Of Contents
- ScODA: Supercomputing Operational Data Analytics Database Benchmarking
Abstract
Supercomputers are powerful, complicated, and exepensive national resources. These devices enable researchers to answer basic science research questions through computational modeling, training of foundational scientific deep learning models, and prediction of natural phenomenon. However, these devices are prone to failure, consume significant power and cooling resources, and undergo varying levels of computational load. Thus the system logs, environment sensors, and other monitoring utilities are captured in stored in distributed, parallel databases and lakehouses.
This data enables business intelligence, operations, and high-performance computing (HPC) research teams to access, query, and evaluate the data for different tasks. But as supercomputers scale towards post-exascale computation, the amount of processing power to host, query, and load data into these databases concurrently and in real-time also grows. Thus, ScODA was created as a pipeline to evaluate different database and lakehouse solutions on real and synthetic environmental data from supercomputing facilities.
System Dependencies
Using ScODA
Install With pip
Install With pipx
Build From Source
Command Line Options
Leveraging ScODA SQLite3 Database
Contributing To ScODA
Submitting Issues
Submitting Bug Reports
Submitting Incorrect Benchmarks
Submitting Security Patches
Requesting Features
Requesting Benchmarks
Developing Features
Adding Datasets
Adding Databases
Adding Benchmarks
Owner
- Name: Nicholas Synovic
- Login: NicholasSynovic
- Kind: user
- Location: Chicago, IL
- Website: https://nicholassynovic.github.io/
- Repositories: 89
- Profile: https://github.com/NicholasSynovic
Loyola University Chicago Computer Science Student Expected Graduation: May 2022
Citation (CITATION.cff)
# https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-citation-files
GitHub Events
Total
- Push event: 62
- Create event: 4
Last Year
- Push event: 62
- Create event: 4
Dependencies
- adminer 5.3.0
- mysql 9.3.0
- postgres 17.5
- matplotlib >=3.10.3
- pandas >=2.3.0
- psycopg2-binary >=2.9.10
- pymysql >=1.1.1
- pyspark >=4.0.0,<5
- sqlalchemy >=2.0.41
- streamlit >=1.46.1
- poetry *
- altair 5.5.0
- attrs 25.3.0
- blinker 1.9.0
- cachetools 6.1.0
- certifi 2025.6.15
- charset-normalizer 3.4.2
- click 8.2.1
- colorama 0.4.6
- contourpy 1.3.2
- cycler 0.12.1
- fonttools 4.58.4
- gitdb 4.0.12
- gitpython 3.1.44
- greenlet 3.2.3
- idna 3.10
- jinja2 3.1.6
- jsonschema 4.24.0
- jsonschema-specifications 2025.4.1
- kiwisolver 1.4.8
- markupsafe 3.0.2
- matplotlib 3.10.3
- narwhals 1.45.0
- numpy 2.3.1
- packaging 25.0
- pandas 2.3.0
- pillow 11.3.0
- protobuf 6.31.1
- psycopg2-binary 2.9.10
- py4j 0.10.9.9
- pyarrow 20.0.0
- pydeck 0.9.1
- pymysql 1.1.1
- pyparsing 3.2.3
- pyspark 4.0.0
- python-dateutil 2.9.0.post0
- pytz 2025.2
- referencing 0.36.2
- requests 2.32.4
- rpds-py 0.25.1
- scoda 0.0.0
- six 1.17.0
- smmap 5.0.2
- sqlalchemy 2.0.41
- streamlit 1.46.1
- tenacity 9.1.2
- toml 0.10.2
- tornado 6.5.1
- typing-extensions 4.14.0
- tzdata 2025.2
- urllib3 2.5.0
- watchdog 6.0.0